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https://github.com/ynstf/real-time-table-segmentation-and-line-extraction-with-opencv

Effortlessly segment tables and extract lines in real-time with this OpenCV-based project. Enhance your image processing capabilities for accurate table recognition. Seamless integration of Flask, Socket.IO, and Watchdog ensures a user-friendly experience.
https://github.com/ynstf/real-time-table-segmentation-and-line-extraction-with-opencv

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Effortlessly segment tables and extract lines in real-time with this OpenCV-based project. Enhance your image processing capabilities for accurate table recognition. Seamless integration of Flask, Socket.IO, and Watchdog ensures a user-friendly experience.

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# Table Line Detection with OpenCV

This repository contains a Python script for detecting lines in tables using OpenCV. The script uses techniques such as edge detection, Hough Line Transform, and k-means clustering to identify and draw horizontal and vertical lines in an input image.

![cases extraction](https://github.com/ynstf/Real-time-Table-Segmentation-and-Line-Extraction-with-OpenCV/assets/107154559/8c41f1b7-9df5-4a1a-ac17-4fd1052ce9f8)

## Features

- Detects and visualizes horizontal and vertical lines in tables.
- Adjustable parameters using trackbars for vertical and horizontal line spacing.
- Real-time visualization of the line detection with OpenCV windows.

## Getting Started

### Prerequisites

- Python
- OpenCV
- NumPy
- scikit-learn

```
pip install opencv-python numpy scikit-learn
```

### Usage

1. Clone the repository:

```
git clone https://github.com/ynstf/Real-time-Table-Segmentation-and-Line-Extraction-with-OpenCV.git
cd Real-time-Table-Segmentation-and-Line-Extraction-with-OpenCV
```

2. Run the script:

```
python main.py
```

## Acknowledgments

- The script uses OpenCV and scikit-learn for image processing and k-means clustering.